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Record W4410313777 · doi:10.32920/ifmj.v4i1-2.1967

Committed Documentary Practices in Digital Media Cultures

2024· article· en· W4410313777 on OpenAlexvenueno aff
Jasmin Kermanchi

Bibliographic record

VenueInteractive Film and Media Journal · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDigital mediaMedia studiesSociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Committed documentary practices designed with and for marginalized people and those affected by social problems have a long tradition. Digital media cultures seem to offer new opportunities for participation and community building along with new forms of expression that can potentially create cultural visibility for marginalized positions on a global level. This contribution argues that in engaged interactive documentary projects on the web (i-docs), communal experiences and counterpublics that respond to social and cultural exclusion mechanisms are closely related. The focus is on projects that offer space for dialog and are also called “open space documentaries” (Zimmermann/de Michiel 2018). To collectively demand one's participation in the public sphere and dominant culture through DOING documentary can foster the feeling of being part of a (virtual) community. Emerging ‘we-groups’ with democratic goals articulate marginalized positions in the form of counterpublics and seek to address an outside audience with their counterpublic discourses. However, the shared aesthetic practices and communicative narrative processes that form the basis of communal experiences are not always conducive to cultural participation and democratic participation in the public sphere. This presentation examines the relationship between demanding one's socio-cultural participation and community experiences in committed participatory i-docs. The hypothesis is that group-specific goals are difficult to reconcile with promoting the cultural and democratic participation of those affected by social problems – meaning cultural forms of democracy. The theoretical framework first discusses the prerequisites for cultural participation and participation in the public sphere, including media-philosophical approaches such as those of Jacques Rancière (2010) or Michaela Ott (2018) and theories of democracy and the public sphere such as those of Chantal Mouffe (2013) and Nancy Fraser (1990). In addition, the contribution clarifies what distinguishes a (virtual) community from communal experiences (Deterding 2009). Then, three committed i-docs that promote communal experiences and try to challenge dominant cultural and societal structures serve as examples in this media studies investigation: Dadaab Stories (2013), Question Bridge: Black Males (2012), The G Word: Transforming Gender Norms, One Story at a Time (2015). The study uses media-aesthetic and content analyses of the i-docs as well as praxeological analyses of their processes conducted based on paratexts and interviews to examine communal experiences and to identify the potential for counter-narratives that deconstruct stereotypes and disseminate positions that are culturally almost invisible. The three i-docs show that the self-representation of marginalized participants and sharing their experiences can be useful for a sense of community but are not always sufficient for challenging dominant images and identity attributions. The presentation argues that an unreflected handling of stereotypical self-images, for example, prevents the promotion of participation. People affected by social problems are usually not in the position to reflect on their representation on a meta-level. A conclusion regarding further research suggests differentiating between forms of active media participation and passive cultural or democratic participation or participation in a (virtual) community instead of euphorically equating these forms by hastily ascribing political potential to the act of taking part in a media project.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.288
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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